Current and ongoing projects.
2023:view paper
The paper explores the performance of classical machine learning algorithms on small and imbalanced datasets by predicting the winner of the TV series RuPaul’s Drag Race using binary classification. Algorithms include: Logistic Regression, Naive-Bayes, Decision Trees, and Random Forest . The paper discusses and demonstrates hyperparameter tuning techniques and various cross validation approaches to identify the most performative classifier for the dataset.
2022: view notebook
The project discusses the architecture of Weaviate, an open-source vector database and provides a tutorial implementation of a custom vector search engine using Weaviate Cloud Service (WCS). The project explores the HNSW (Hierarchical Navigable Small World) graph-based index for vector similarity search, dimensionality reduction techniques (PCA, t-SNE, and UMAP) for visualization, and various other features of Weaviate.
2022: view repo
Data visualization of the taxonomic relationships of the trees on Oahu, Hawaii. The tree data is sourced from Exceptional Trees on Oahu API, and Wikipedia.
2022: view paper
This paper discusses and applies node-based centrality metrics to perform network analysis on a sample of the Ethereum Network. Centrality metrics, such as degree centrality, eigenvector centrality, Katz centrality and PageRank are used to identify influential contract addresses in the Ethereum ecosystem.
2021: view project
Independent RPi cluster-build and distributed computing project
2019: view project
QTPOC film, art and mental health project based in Ithaca, NY